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2024 | OriginalPaper | Buchkapitel

Generic Medicine Recommender System with Incorporated User Feedback

verfasst von : Sneh Shah, Varsha Naik, Debajyoti Mukhopadhyay, Swapnoneel Roy

Erschienen in: Internet of Things. Advances in Information and Communication Technology

Verlag: Springer Nature Switzerland

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Abstract

This paper presents the implementation of a Generic Medicine Recommender System (GMRS) that incorporates user feedback as a solution to streamline the selection process of appropriate generic medication and improve overall quality of healthcare. The study evaluates the suggestions given by the Generic Medicine Recommender System (GMRS), enhance the suggestions based on user input, and comprehend the influence of these suggestions on patient outcomes following the usage of generic medications. The results imply that the GMRS not only has the potential to enhance patient outcomes but can also give important information about the efficacy of various generic medications. The study also emphasizes how critical it is to incorporate user input into system recommendations in order to maximize performance and the system’s effect on healthcare expenses. Recommending generic alternatives to costly prescribed medicines is significant because in addition to ensuring the provision of more broadly accessible drugs for treatment, it assists patients in saving money on their prescription pharmaceuticals. Generic medications have the same amounts of active ingredients as branded drugs. As a result, when it comes to treating sickness, generic medications are often as effective as branded medications.

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Metadaten
Titel
Generic Medicine Recommender System with Incorporated User Feedback
verfasst von
Sneh Shah
Varsha Naik
Debajyoti Mukhopadhyay
Swapnoneel Roy
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-45882-8_5